CN117114379A

CN117114379A - Multi-field bridge task scheduling method, device and equipment in storage yard and storage medium

Info

Publication number: CN117114379A
Application number: CN202311389749.5A
Authority: CN
Inventors: 栾垚; 贾庆山; 王腾飞; 李智宇
Original assignee: Tsinghua University; CRSC Research and Design Institute Group Co Ltd
Current assignee: Tsinghua University; CRSC Research and Design Institute Group Co Ltd
Priority date: 2023-10-25
Filing date: 2023-10-25
Publication date: 2023-11-24
Anticipated expiration: 2043-10-25
Also published as: CN117114379B

Abstract

The specification relates to the field of field bridge scheduling methods and provides a method, a device, equipment and a storage medium for scheduling multi-field bridge tasks in a storage yard. The method comprises the following steps: when each decision period starts, acquiring the characteristics of all schedulable carrying tasks in the decision period and a first task sequence which is not executed and completed in the last decision period; based on the characteristics, distributing a field bridge for all schedulable transport tasks of the decision period; sequencing the tasks in each field bridge by calling a traveling business problem solving algorithm to obtain a second task sequence of each field bridge; and correspondingly splicing the second task sequence of each field bridge to the end of the first task sequence of each field bridge to obtain the total task sequence of each field bridge in the decision period. The field bridge task allocation method provided by the embodiment of the specification can eliminate the constraint that the field bridges cannot cross each other, so that the optimization problem can be decoupled to each field bridge, and the solving efficiency is improved.

Description

Multi-field bridge task scheduling method, device and equipment in storage yard and storage medium

Technical Field

The present disclosure relates to the field of field bridge scheduling methods, and in particular, to a method, an apparatus, a device, and a storage medium for scheduling multiple field bridge tasks in a storage yard.

Background

The yard is an important transfer node for connecting ocean transportation and railway transportation in the sea-iron intermodal transportation, is an important bottleneck of cargo transfer efficiency, and the storage expense to be paid by a cargo owner is also related to the storage time of a container in the yard, so that the improvement of the yard transfer efficiency is beneficial to improving the sea-iron intermodal transportation efficiency and reducing the cost of the cargo owner. The transit time of a container in a yard, i.e., the total time it takes for a yard bridge to complete the handling of all containers. Two or more field bridges running on the same guide rail are usually arranged in a railway yard, and the field bridges cannot cross each other. Each bridge is respectively responsible for part of the container handling tasks, and the processes of the carrying out tasks of the bridges are parallel, so that the total time spent for carrying all the containers is the maximum value of the time spent for each bridge to complete the part of the handling tasks. Compared with the single-field bridge situation, the problem of task allocation among the field bridges in the multi-field bridge situation can not mutually pass through, so that the accurate solution of the optimal scheduling scheme is particularly difficult.

At present, the field bridge scheduling method mainly comprises three types: scheduling method based on heuristic rule, method based on optimization problem solving and method based on rolling optimization. The scheduling method based on heuristic rules mainly adopts a nearest neighbor strategy, a first-come first-serve strategy and the like to schedule tasks, and the method has high execution efficiency, but the rules need to be manually specified in advance and lack performance guarantee. The method for solving the optimization problem models the field bridge scheduling problem as a mixed integer programming problem, and schedules tasks by setting up an objective function, so that the method has better performance guarantee, but the method has the problems of more constraint and large calculation amount, and is difficult to meet the real-time requirement. The rolling optimization-based method adopts the idea of model predictive control, and only performs a small part of the method for a long decision period, discards the rest part, and wastes a large amount of computing resources.

Disclosure of Invention

In order to solve the above-mentioned problems, an object of the present disclosure is to provide a method for scheduling multi-bridge tasks in a yard, so as to overcome the above-mentioned problems or at least partially solve the above-mentioned problems.

In one aspect, some embodiments of the present disclosure provide a method for scheduling a multi-bridge task in a yard, the method including:

when each decision period starts, acquiring the characteristics of all schedulable carrying tasks in the decision period and a task sequence which is not executed in a decision period on each field bridge, and taking the task sequence as a first task sequence of each field bridge;

based on the characteristics, distributing a field bridge for all schedulable transport tasks of the decision period;

sequencing schedulable carrying tasks in each field bridge by calling a traveling business problem solving algorithm to obtain a second task sequence of each field bridge;

and correspondingly splicing the second task sequence of each field bridge to the end of the first task sequence of each field bridge to obtain the total task sequence of each field bridge in the decision period.

Further, the allocating a field bridge for all the schedulable transport tasks of the decision period includes:

selecting a field bridge task division threshold value which is one less than the field bridge in number in the direction perpendicular to the field bridge guide rail according to the field bridge number;

Dividing the storage yard into a plurality of areas with the same number of field bridges by taking the position of the threshold as a limit;

a field bridge is allocated to each of the regions on a nearest neighbor basis.

Further, the selecting a field bridge task division threshold value which is one less than the field bridge in the direction perpendicular to the field bridge guide rail includes:

enumerating the number of columns of the discharged containers in the storage yard, and taking the number of columns as candidate dividing thresholds;

simulating to obtain the time for all the field bridges to finish all the carrying tasks under the candidate division threshold;

selecting a candidate division threshold with the shortest finishing time as an optimal division threshold;

taking the characteristics of the schedulable carrying tasks, the positions of the field bridges and the time for completing all carrying tasks of all the field bridges as inputs of a classifier, and outputting the probability of taking each candidate division threshold as an optimal division threshold;

and selecting the candidate threshold with the maximum probability as an optimal dividing threshold.

Further, the processing logic of the classifier includes:

the characteristics of the schedulable transport task are flattened into a one-dimensional vector after passing through two convolution layers in sequence, and the schedulable transport task characteristic vector is obtained after passing through a full connection layer;

The vector formed by splicing the position coordinates of each field bridge passes through a full-connection layer to obtain a field bridge position vector;

splicing the characteristic vector of the schedulable carrying task and the position vector of the field bridge, and obtaining a spliced vector after a full connection layer;

and obtaining the probability that each division threshold is the optimal division threshold through an activation function according to the spliced vector.

Further, the traveling salesman problem solving algorithm includes an LKH-3 solver, and the calling the traveling salesman problem solving algorithm sorts the schedulable carrying tasks in each field bridge, including:

randomly selecting an initial task order;

calculating the time spent for carrying the schedulable tasks according to the initial task ordering;

adjusting the sequence of the initial task sequencing, and simultaneously calculating the time spent by the adjusted sequencing when carrying the schedulable tasks;

if the time spent by the task handling of the adjusted task sequence is less than the time spent by the task handling according to the initial task sequence, replacing the initial sequence with the adjusted task sequence;

and traversing all schedulable carrying tasks until the task sequence is no longer updated and outputting a final task sequence.

Further, after obtaining the total task sequence of each field bridge in the decision period, the method further comprises:

judging whether cross conflict occurs between two adjacent field bridges according to the total task sequence of each field bridge;

if the conflict occurs, the scheduling of the corresponding field bridge is adjusted according to the total time for the adjacent two field bridges with the cross conflict to complete the task.

Further, judging whether collision occurs between two adjacent field bridges according to the total task sequence of each field bridge, including:

acquiring the moving speed of each field bridge;

obtaining the position of each schedulable carrying task according to the characteristics;

calculating the moving time of each field bridge according to the total task sequence of each field bridge and the moving speed of the field bridge;

obtaining a graph of the change of the position coordinates of each field bridge along with time according to the position and the moving time of each field bridge;

if the curve intersection exists on the graph, judging that the intersection conflict exists between the field bridges corresponding to the curve, otherwise, judging that the intersection conflict does not exist.

Further, adjusting the scheduling of the corresponding field bridge according to the total time for the two adjacent field bridges with cross conflict to complete the task, including:

Respectively solving the total time spent by the two adjacent bridges in completing the tasks in the total task sequence;

when cross conflict occurs, firstly executing the task for which the field bridge with larger total time is responsible at the moment, moving the field bridge with smaller total time to a safe distance for avoidance, and recording the time spent in the avoidance process;

checking whether the field bridge with smaller total time generates cross conflict with the field bridge with the largest total time in the process of executing the next task;

if collision occurs, the field bridge with smaller total time spends avoiding the field bridge with the largest total time spending, does not execute the next task, moves to a safe distance to avoid, and records the extra time spent by the field bridge with smaller total time spending due to avoidance;

if no conflict occurs, the field bridge with smaller total time continues to normally execute the next task in the total task sequence;

updating the total time spent by the two bridges to complete the task;

the above process is repeated until all tasks of both field bridges are performed.

In another aspect, some embodiments of the present disclosure further provide an in-yard multi-bridge task scheduling apparatus, where the apparatus includes:

The characteristic acquisition module is used for acquiring the characteristics of all schedulable carrying tasks in each decision period and the task sequence which is not executed in the last decision period of each field bridge and is completed in the decision period when each decision period starts, and taking the characteristics as a first task sequence of each field bridge;

the task allocation module is used for allocating a field bridge for all the schedulable carrying tasks in the decision period based on the characteristics;

the task sequencing module is used for sequencing the schedulable carrying tasks in each field bridge to obtain a second task sequence of each field bridge;

and the task sequence determining module is used for correspondingly splicing the second task sequence of each field bridge to the end of the first task sequence of each field bridge to obtain the total task sequence of each field bridge in the decision period.

In another aspect, some embodiments of the present description also provide a computer device including a memory, a processor, and a computer program stored on the memory, which when executed by the processor, performs the instructions of the above method.

In another aspect, some embodiments of the present description also provide a computer storage medium having stored thereon a computer program which, when executed by a processor of a computer device, performs instructions of the above method.

In another aspect, some embodiments of the present description also provide a computer program product comprising a computer program which, when executed by a processor of a computer device, performs instructions of the above method.

One or more technical solutions provided in some embodiments of the present disclosure at least have the following technical effects:

according to the embodiment of the specification, the characteristics of the schedulable task in each decision period and the task sequence which is not executed and completed in the last decision period are automatically acquired, and the field bridges are allocated to the schedulable task based on the characteristics. And then calling a traveling business problem solving algorithm to sequence the tasks in each field bridge to obtain a new task sequence of each field bridge, and placing the sequence which is not executed in the last decision period before the new sequence to obtain a total executable task sequence of the field bridge. Compared with the method based on rolling optimization in the prior art, the method can utilize the task sequence which is optimized but not executed in the last decision period, and saves the computing resources.

The foregoing description is merely an overview of some embodiments of the present disclosure, which may be practiced in accordance with the disclosure of the present disclosure, for the purpose of making the foregoing and other objects, features, and advantages of some embodiments of the present disclosure more readily apparent, and for the purpose of providing a more complete understanding of the present disclosure's technical means.

Drawings

In order to more clearly illustrate the embodiments of the present description or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments described in the present description, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art. In the drawings:

FIG. 1 is a flowchart of a multi-bridge task scheduling method in a yard according to an embodiment of the present disclosure;

FIG. 2 is a schematic diagram showing the steps for allocating a field bridge for all dispatchable transportation tasks for each decision period in the embodiment of the present disclosure;

FIG. 3 is a schematic diagram of a two-field bridge task partitioning algorithm in a yard according to an embodiment of the present disclosure;

Fig. 4 is a schematic diagram showing steps of determining whether a collision occurs between two neighboring field bridges according to the total task sequence of each field bridge in the embodiment of the present disclosure;

5 (a) -5 (d) are graphs showing the position of two field bridges over time during a partial decision period in which there is a field bridge cross collision in the embodiment of the present specification;

6 (a) -6 (b) are graphs showing the position of two field bridges over time during a partial decision period in which there is no cross collision of the field bridges in the embodiments of the present specification;

fig. 7 is a schematic structural diagram of a task scheduling device for multiple bridges in a storage yard according to an embodiment of the present disclosure;

fig. 8 is a schematic diagram of a computer device provided in some embodiments of the present disclosure.

[ reference numerals description ]

701. A feature acquisition module;

702. a task allocation module;

703. a task ordering module;

704. a task sequence determining module;

802. a computer device;

804. a processor;

806. a memory;

808. a driving mechanism;

810. an input/output interface;

812. an input device;

814. an output device;

816. a presentation device;

818. a graphical user interface;

820. a network interface;

822. a communication link;

824. A communication bus.

Detailed Description

In order to make the technical solutions in the present specification better understood by those skilled in the art, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is obvious that the described embodiments are only some embodiments of the present specification, not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are intended to be within the scope of the present disclosure.

It should be noted that the terms "first," "second," and the like in the description and claims herein and in the foregoing figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the present description described herein may be capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, apparatus, article, or device that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed or inherent to such process, method, article, or device. It should be noted that, in the technical scheme of the application, the acquisition, storage, use, processing and the like of the data all conform to the relevant regulations of national laws and regulations.

Fig. 1 is a flowchart of a method for scheduling multi-yard bridge tasks in a storage yard according to an embodiment of the present disclosure, which provides the method operational steps described in the examples or flowcharts, but may include more or fewer operational steps based on conventional or non-inventive labor. The order of steps recited in the embodiments is merely one way of performing the order of steps and does not represent a unique order of execution. The method may include:

101: when each decision period starts, acquiring the characteristics of all schedulable carrying tasks in the decision period and a task sequence which is not executed in a decision period on each field bridge, and taking the task sequence as a first task sequence of each field bridge;

102: based on the characteristics, distributing a field bridge for all schedulable transport tasks of the decision period;

103: sequencing schedulable carrying tasks in each field bridge by calling a traveling business problem solving algorithm to obtain a second task sequence of each field bridge;

104: and correspondingly splicing the second task sequence of each field bridge to the end of the first task sequence of each field bridge to obtain the total task sequence of each field bridge in the decision period.

In some embodiments, the decision period is defined as the interval between two adjacent changes in the movement task that begin with the arrival of a particular vessel or train and end with the arrival of the next vessel or train. The characteristics of the schedulable transport tasks include the location of the transport task and the type of transport task. The position of the carrying task is a storage yard coordinate (x, y, z), the x direction is parallel to the field bridge guide rail direction, the y direction is perpendicular to the field bridge guide rail direction, and the z direction is a height. The types of the carrying tasks include: the collection card is transported into a storage yard, transported out of the storage yard to a train, and directly transported to the train. And the task sequences which are not executed and completed in the last decision period are arranged according to the execution sequence determined in the last decision period. Before each decision period begins, all dispatchable transfer tasks characteristic of the decision period are acquired according to the current day cargo ship or train transportation plan. The arrival of each cargo ship or train is taken as an event, and the unequal division of the width of the time window is realized by combining an event-driven scheme, so that the calling frequency of a scheduling algorithm is increased when the cargoes arrive densely, the problem scale of single scheduling is reduced, and the algorithm cannot be effectively solved because the number of tasks to be scheduled in a single time window is too large and too complex.

Referring to fig. 2, in some embodiments, the allocation of a field bridge for all schedulable transport tasks for this decision period may include:

201: selecting a field bridge task division threshold value which is one less than the field bridge in number in the direction perpendicular to the field bridge guide rail according to the field bridge number;

202: dividing the storage yard into a plurality of areas with the same number of field bridges by taking the position of the threshold as a limit;

203: a field bridge is allocated to each of the regions on a nearest neighbor basis.

The cross constraint of the field bridge and the related constraint of task allocation are important constraints for coupling the scheduling problem of multiple field bridges, and the task allocation formula is realized because the field bridge moves along the direction of the guide rail (x direction)The method can completely divide the area in charge of each field bridge, and ensures that the field bridges are not crossed in the whole operation process. Under the allocation method, the original multi-field-bridge joint scheduling problem is not coupled any more, the scheduling problem of each field bridge is changed into the problem of independent scheduling, the scheduling of a single field bridge is equivalent to the problem of an asymmetric tourist, and the existing algorithm can obtain better effects. Preferably, taking the dispatch of a dispatch-based transport task for two bridges as an example, as shown in fig. 3, a partition threshold x is selected in a direction perpendicular to the bridge rails ₀ And dividing the storage yard into two areas by taking the position of the dividing threshold as a limit. Since field bridge 1 is closer to the left region and field bridge 2 is closer to the right region, all position coordinates are satisfied with x according to the principle of proximity<x0 container handling tasks are assigned to field bridge 1 and the remaining container handling tasks are assigned to field bridge 2. Under the condition that the box turning does not exist and the moving time of the field bridge depends on the moving time of the field bridge in the x direction, for any allocation method which does not meet the task allocation rule, always the task with the maximum x in the tasks allocated by the field bridge 1 and the task with the minimum x in the tasks allocated by the field bridge 2 can be exchanged, the process is repeated, and finally the allocation method which meets the task allocation rule is approximately obtained, so that the task allocation method has certain performance guarantee.

Referring to fig. 3, taking a field bridge scheduling of two field bridges as an example, the selecting a field bridge task division threshold value that is one less than the number of field bridges in a direction perpendicular to a field bridge rail may include:

enumerating the number of columns of stacked containers in the storage yard, wherein in the embodiment, the number of columns is 9, each column represents a group of box numbers, each box number stores a group of containers, and the position of each column of box numbers in the x direction is taken as a candidate division threshold value and expressed as a set ；

The method comprises the steps of enumerating the number of columns of the discharged containers in a storage yard, taking the number of columns as candidate division thresholds, simulating to obtain the time for all the bridges to finish all the carrying tasks under the candidate division thresholds, and selecting the candidate division threshold with the shortest finishing time as an optimal division threshold, wherein an optimal solution can be obtained in theory, but real-time requirements in practical problems are difficult to meet. The candidate dividing threshold value, the characteristic of the schedulable carrying task, the position of the field bridge and the time of all the field bridges completing all the carrying tasks obtained from the enumeration method are used as data sets, a supervised learning method is used for training a classifier, and a mapping of vectors formed by the probability that each candidate dividing threshold value is used as an optimal dividing threshold value from the characteristics of the storage yard is fitted. In practical application, the characteristics of the schedulable carrying task are input into a trained model, the model outputs each candidate division threshold as the probability of the optimal division threshold, and the candidate division threshold with the highest probability is selected as the optimal division threshold. Further, the process of training the classifier by using the supervised learning method may be a currently mainstream method, which is not limited in this specification.

Preferably, in the embodiment of the present specification, the process of training the classifier using the supervised learning method may include the following steps:

step a: reading a data set collected by the enumeration method;

step b: initializing a classifier and an optimizer, wherein an Adam optimizer is selected in the implementation process of the specification;

step c: designating the number of training wheels;

step d: extracting a plurality of pieces of data from a data set in each round of training, wherein each piece of data comprises a storage yard characteristic (input) and a vector (label) formed by the probability that each dividing position x is taken as an optimal dividing position;

step e: inputting the characteristic of the schedulable transport task into a classifier to obtain a prediction result;

step f: and solving cross entropy loss according to the prediction result and the data label, carrying out gradient back propagation on the loss, and updating classifier parameters by using an optimizer.

Further, the classifier may be any classifier currently in the mainstream, which is not limited in this specification. Preferably, in an embodiment of the present disclosure, the processing logic of the classifier may include:

and obtaining the probability that each division threshold is the optimal division threshold through an activation function by the spliced vector.

In some embodiments, the traveler problem solving algorithm includes an LKH-3 solver, and the invoking the traveler problem solving algorithm orders the schedulable transport tasks in each of the field bridges includes:

randomly selecting an initial task order;

It will be understood that, with each task assigned to each bridge as a path point, the distance between two tasks a and b is defined as the time for the bridge to complete task a and the time required for the bridge to move from the ending point of task a to the starting point of task b, and this distance is asymmetric, so the process of ordering the assigned tasks by the bridge can be regarded as an asymmetric travel provider problem (ats), and the assigned tasks are ordered by invoking the ats solving method. Further, the ats solving method may be a simulated annealing algorithm, a genetic algorithm, an ant colony algorithm, a tabu search algorithm, or the like, which is not limited in this specification. Preferably, the LKH-3 solver is selected in the embodiments of the present description to order the assigned tasks in the field bridge. The LKH solver is a better algorithm for solving the problem of traveling business at present, and based on the Lin-Kernighan idea, the optimal path solution is continuously improved and obtained by cutting off and reconnecting the connecting edges of the path points. The LKH-3 solver is used as an extension of the LKH solver, and has higher solving efficiency.

Further, in some embodiments, after obtaining the total task sequence of each field bridge in the decision period, the method may further include:

Referring to fig. 4, in some embodiments, determining whether a collision occurs between two neighboring field bridges according to the total task sequence of each field bridge may include the following steps:

401: and acquiring the moving speed of each field bridge. Specifically, the moving speed of the field bridge is preset, is expressed as a vector, comprises the average speed of the field bridge in three directions in the running process, and moves at a uniform speed;

402: obtaining the position of each schedulable carrying task according to the characteristics;

403: calculating the moving time of each field bridge according to the total task sequence of each field bridge and the moving speed of the field bridge;

404: and obtaining a graph of the position coordinates of each field bridge along with time according to the position and the moving time of each field bridge. Specifically, Z is the maximum number of stacked bins per stack. The current position of the recording bridge isThe position of the container to be carried is +. >Respectively need to be transported to +.>I.e. the position is +.>The container is to be transported to the location +.>I is->. Firstly, acquiring a field bridge key point sequence according to the current position and the target position of each container: />For each track segment +.>The method comprises the following 3 moving stages in sequence:

1) Ascending:the time spent is: />* The box height/field bridge z-direction speed;

2) And (3) horizontally moving:the time spent is: />Wherein->* Case bit x-direction length/field bridge x-direction speed, < >>* The length of the box y direction/the speed of the field bridge y direction;

3) And (3) descending:the time spent is: />* The box height/field bridge z-direction speed;

the horizontal movement time takes the time maximum value of the x and y directions because the field bridges can move simultaneously in the x and y directions, but partial field bridges cannot move simultaneously in the x and y directions, and the partial field bridges are considered respectively.

In particular, whenAnd->In this case, the moving process of the field bridge can be simplified as follows:the time spent is: />* The box height/field bridge z-direction speed.

In addition, for the container transporting task, after the moving part is finished, the container turning track is calculated, and for the container to be transported outThe box turning position is positioned at +.>Here, z=0 is because the case-turning position needs to be emptied after each use, and the case-turning process includes the following steps:

1) Each container above the container to be transportedIs transported to the box turning areaWherein->；

2) To be transported out of the containerMove to the delivery position->；

3) Each container in the box turning areaCarry back->。

The moving time of the box turning process is calculated as before, and a complete x-t curve of the field bridge can be obtained according to the process.

S405: if the curve intersection exists on the curve graph, judging that the intersection conflict exists between the field bridges corresponding to the curve graph, otherwise, judging that the intersection conflict does not exist.

Fig. 5 (a) -5 (d) are schematic diagrams of the position changes over time of two field bridges in the partial decision period where there is a cross collision of the field bridges in the embodiment of the present specification, and the abscissa is time, the unit is minutes, and the ordinate is the x-coordinate of the field bridge. Fig. 5 (a) and fig. 5 (b) respectively show x-t graphs of two field bridges before and after the adjustment of the field bridge scheduling after the cross collision occurs in one embodiment, and a portion of the field bridge x-t graph in fig. 5 (a) with a dotted line below a solid line indicates that the cross collision occurs in the two field bridges, and a portion of the graph with the dotted line below the solid line after the adjustment and scheduling does not exist, which indicates that the cross collision does not exist at this time. Fig. 5 (c) and fig. 5 (d) are x-t graphs respectively showing the adjustment of the two field bridges before and after the field bridge scheduling after the cross collision in another embodiment. Fig. 6 (a) -6 (b) are schematic diagrams of the position changes over time of two field bridges in the partial decision period where there is no cross collision of the field bridges in the embodiment of the present specification, and the abscissa is time, the unit is minutes, and the ordinate is the x-coordinate of the field bridge. Wherein fig. 6 (a) shows an x-t graph of a two-field bridge without cross collision in one embodiment, and fig. 6 (b) shows an x-t graph of a two-field bridge without cross collision in another embodiment, it can be seen from the figure that there is no portion of the dashed line below the solid line, which indicates that there is no cross collision, and only the task needs to be executed according to the original task sequence.

In some embodiments, adjusting the scheduling of each field bridge according to the total time for each field bridge to complete the task may include the steps of:

step a: respectively solving the total time spent by the two adjacent bridges in completing the tasks in the total task sequence;

step b: when cross conflict occurs, firstly executing the task for which the field bridge with larger total time is responsible at the moment, moving the field bridge with smaller total time to a safe distance for avoidance, and recording the time spent in the avoidance process;

wherein the safety distance is preset, and generally refers to the minimum distance between two field bridges on the guide rail; the field bridge which takes a longer time is described asThe field bridge taking less total time is denoted +.>On-site bridge->After the target position of (2) is fixed, field bridge->Move to distance field bridge->Waiting for a position at a target position safe distance;

step c: checking the field bridgeWhether or not the next task will be executed in conjunction with the field bridge>Generating cross conflict;

step d: if a conflict occurs, the field bridgeAvoiding the field bridge->Without performing the next task, move to safe distance to avoid and record the field bridge +.>Time spent additionally due to avoidance;

In particular, the additional time spent for avoidance is not just a field bridgeThe time required for the moving process to move to the safe distance and the waiting process to avoid; for example, assume +.>Currently at x=3, the original next target position is at x=6, +.>It takes only 3 units of time to move from the current position to the target position. However, to avoid another bridge needs to first move to x=1, wait 2 units of time at x=1, and then move from 1 to 6, and take 2+5+2=9 units of time, so the additional time spent for avoiding is (2+5+2) -3=6, instead of just moving toSafe distance this movement and the time required to avoid this waiting process, i.e. 2+2=4;

step e: if no conflict occurs, the field bridge with smaller total time continues to normally execute the next task in the total task sequence;

step f: updating the two-bridge takes the total time to complete the task.

Specifically, the total time spent for completing the task is dynamically changed, and after each time the field bridge performs avoidance, the total time spent for completing the task of the two field bridges is recalculated by adding the extra time spent by the field bridge due to avoidance, so that the field bridge with smaller total time spent is dynamically changed along with the update of the total time spent.

The present specification provides method operational steps as described in the examples or flowcharts, but may include more or fewer operational steps based on conventional or non-inventive labor. The order of steps recited in the embodiments is merely one way of performing the order of steps and does not represent a unique order of execution. When a system or apparatus product in practice is executed, it may be executed sequentially or in parallel according to the method shown in the embodiments or the drawings.

Corresponding to the above-mentioned method for scheduling multi-field bridge tasks in a storage yard, some embodiments of the present disclosure further provide a device for scheduling multi-field bridge tasks in a storage yard, as shown in fig. 7, and in some embodiments, the device may include:

the feature obtaining module 701 is configured to obtain, when each decision period starts, features of all schedulable carrying tasks in the decision period and a task sequence that is not performed in a decision period on each bridge, and take the task sequence as a first task sequence of each bridge;

a task allocation module 702, configured to allocate a field bridge for all the schedulable transport tasks in the decision period;

A task ordering module 703, configured to order the schedulable transport tasks in each field bridge, so as to obtain a second task sequence of each field bridge;

and the task sequence determining module 704 is configured to splice the second task sequence of each field bridge to the end of the first task sequence of each field bridge, so as to obtain a total task sequence of each field bridge in the decision period.

The user information (including but not limited to user equipment information, user personal information, etc.) and the data (including but not limited to data for analysis, stored data, presented data, etc.) related to the present application are information and data authorized by the user or sufficiently authorized by each party.

As shown in fig. 8, which is a schematic diagram illustrating the structure of nodes in the side-chain network and nodes in the main-chain network in this embodiment, the structure may include a relay node, a decision maker node, or other functional nodes, which are referred to as computer devices in this embodiment, and the computer device 802 may include one or more processors 804, such as one or more Central Processing Units (CPUs), each of which may implement one or more hardware threads. The computer device 802 may also include any memory 806 for storing any kind of information, such as code, settings, data, etc. For example, and without limitation, memory 806 may include any one or more of the following combinations: any type of RAM, any type of ROM, flash memory devices, hard disks, optical disks, etc. More generally, any memory may store information using any technique. Further, any memory may provide volatile or non-volatile retention of information. Further, any memory may represent fixed or removable components of computer device 802. In one case, the computer device 802 may perform any of the operations of the associated instructions when the processor 804 executes the associated instructions stored in any memory or combination of memories. The computer device 802 also includes one or more drive mechanisms 808, such as a hard disk drive mechanism, an optical disk drive mechanism, and the like, for interacting with any memory.

The computer device 802 may also include an input/output module 810 (I/O) for receiving various inputs (via an input device 812) and for providing various outputs (via an output device 814). One particular output mechanism may include a presentation device 816 and an associated Graphical User Interface (GUI) 818. In other embodiments, input/output module 810 (I/O), input device 812, and output device 814 may not be included, but merely as a computer device in a network. The computer device 802 may also include one or more network interfaces 820 for exchanging data with other devices via one or more communication links 822. One or more communications buses 824 couple the above-described components together.

The communication link 822 may be implemented in any manner, such as, for example, through a local area network, a wide area network (e.g., the internet), a point-to-point connection, etc., or any combination thereof. Communication link 822 may include any combination of hardwired links, wireless links, routers, gateway functions, name servers, etc., governed by any protocol or combination of protocols.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), computer-readable storage media and computer program products according to some embodiments of the specification. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processor to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processor, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processor to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processor to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In a typical configuration, a computer device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of computer-readable media.

Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Disks (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computer device. Computer readable media, as defined in the specification, does not include transitory computer readable media (transmission media), such as modulated data signals and carrier waves.

It will be appreciated by those skilled in the art that embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, the present specification embodiments may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present description embodiments may take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.

It should be understood that, in various embodiments of the present disclosure, the sequence numbers of the foregoing processes do not mean the order of execution, and the order of execution of the processes should be determined by the functions and internal logic thereof, and should not constitute any limitation on the implementation of the embodiments of the present disclosure.

It should also be understood that, in the embodiments of the present specification, the term "and/or" is merely one association relationship describing the association object, meaning that three relationships may exist. For example, a and/or B may represent: a exists alone, A and B exist together, and B exists alone. In the present specification, the character "/" generally indicates that the front and rear related objects are an or relationship.

Those of ordinary skill in the art will appreciate that the elements and algorithm steps described in connection with the embodiments disclosed herein may be embodied in electronic hardware, in computer software, or in a combination of the two, and that the various example components and steps have been generally described in terms of function in the foregoing description to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present specification.

It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.

In the several embodiments provided in this specification, it should be understood that the disclosed systems, apparatuses, and methods may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. In addition, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices, or elements, or may be an electrical, mechanical, or other form of connection.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purposes of the embodiments of the present description.

In addition, each functional unit in each embodiment of the present specification may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on this understanding, the technical solution of the present specification is essentially or a part contributing to the prior art, or all or part of the technical solution may be embodied in the form of a software product stored in a storage medium, including several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in the embodiments of the present specification. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.

The principles and embodiments of the present specification are explained in this specification using specific examples, the above examples being provided only to assist in understanding the method of the present specification and its core ideas; meanwhile, as those skilled in the art will have variations in the specific embodiments and application scope based on the ideas of the present specification, the present description should not be construed as limiting the present specification in view of the above.

Claims

1. The method for scheduling the multi-field bridge tasks in the storage yard is characterized by comprising the following steps of:

2. The method of claim 1, further comprising, after deriving the total task sequence for each field bridge for the decision period:

3. The method according to claim 2, wherein determining whether collision occurs between two neighboring field bridges according to the total task sequence of each field bridge comprises:

acquiring the moving speed of each field bridge;

if the curve intersection exists on the curve graph, judging that the intersection conflict exists between the field bridges corresponding to the curve graph, otherwise, judging that the intersection conflict does not exist.

4. The method of claim 2, wherein adjusting the scheduling of the respective field bridge based on the total time for the adjacent two field bridges that have cross-collisions to complete the task comprises:

updating the total time spent by the two bridges to complete the task;

5. The method of claim 1, wherein said assigning a field bridge for all schedulable transport tasks for the decision period comprises:

a field bridge is allocated to each of the regions on a nearest neighbor basis.

6. The method of claim 5, wherein selecting a field bridge task division threshold that is one less than the number of field bridges in a direction perpendicular to a field bridge rail comprises:

7. The method of claim 6, wherein the processing logic of the classifier comprises:

8. The method of claim 1, wherein the traveler problem solving algorithm comprises an LKH-3 solver, and wherein the invoking the traveler problem solving algorithm orders the schedulable transport tasks in each of the field bridges comprises:

randomly selecting an initial task order;

if the time spent by the task handling of the adjusted task sequence is less than the time spent by the task handling according to the initial task sequence, replacing the initial task sequence with the adjusted task sequence;

9. A multi-bridge task scheduling device in a storage yard, comprising:

the task allocation module is used for allocating a field bridge for all the schedulable transport tasks in the decision period;

10. A computer device comprising a memory, a processor, and a computer program stored on the memory, characterized in that the computer program, when being executed by the processor, performs the instructions of the method according to any of claims 1-8.

11. A computer storage medium having stored thereon a computer program, which, when executed by a processor of a computer device, performs the instructions of the method according to any of claims 1-8.

12. A computer program product, characterized in that the computer program product comprises a computer program which, when being executed by a processor of a computer device, carries out the instructions of the method according to any one of claims 1-8.